Search Results - (( program implementation developing algorithm ) OR ( square optimization method algorithm ))
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Logic Programming In Radial Basis Function Neural Networks
Published 2013“…I used different types of optimization algorithms to improve the performance of the neural networks. …”
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Automated calibration of baseline model for energy conservation using multi-objective Evolutionary Programming (EP) / Ahmad Amiruddin Mohammad Aris
Published 2019“…The proposed co-simulation process is developed by coupling building energy simulation (BES) software, Energy Plus with multi-objective evolutionary programming (MOEP) algorithm which is implemented in Matlab using coupling software, BCVTB. …”
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Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…This optimal state estimate and corrected data base are then used by the security monitoring and operation and control functions of the center.Most state estimation programs in practical use are formulated as overdetermined systems (Pozrikidis, 2008) of nonlinear equations and solved as weighted least square problems (refer to section 2.1.1).This research involves finding the least squares solution of the power system state estimation problem, HTR-1HDx = HTR-1 [z - f (x)] (refer to section 2.3.1) and to develop a program to implement the said algorithm. …”
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An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system
Published 2011“…This paper proposes a new method to trace the transmission loss in deregulated power system by applying Genetic Algorithm (GA) and Least Squares Support Vector Machine (LS-SVM). …”
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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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Structural optimization of 4-DOF agricultural robot arm
Published 2024“…This study studies various optimization algorithms to compare the performance of algorithms that can achieve the optimal length with minimum errors. …”
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Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
Published 2023“…In addition, it also concluded that metaheuristic optimization algorithm and weighted least square method are more suitable to conquer anisotropic factor. …”
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Hybrid particle swarm optimization algorithm with fine tuning operators
Published 2009“…This method combines the merits of the parameter-free PSO (pf-PSO) and the extrapolated particle swarm optimization like algorithm (ePSO). …”
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Implementation of Autonomous Vehicle Navigation Algorithms Using Event-Driven Programming
Published 2012“…By using FSM to describe the behaviour of a navigating mobile robot, an equivalent algorithm can be developed. The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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A new soft computing model for daily streamflow forecasting
Published 2023“…Climate change; Data streams; Floods; Forecasting; Genetic algorithms; Hydroelectric power plants; Mean square error; Multilayer neural networks; Particle swarm optimization (PSO); Soft computing; Soil conservation; Water conservation; Water management; Water supply; Flow quantification; Multi layer perceptron; Optimization algorithms; Predicting models; Root mean square errors; Soft computing models; Streamflow forecasting; Watershed management; Stream flow; algorithm; forecasting method; hydroelectric power plant; numerical model; optimization; principal component analysis; streamflow; watershed; Helianthus…”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…A coati optimization algorithm is introduced to select input scenarios. …”
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Short term traffic forecasting based on hybrid of firefly algorithm and least squares support vector machine
Published 2015“…The goal of an active traffic management is to manage congestion based on current and predicted traffic conditions.This can be achieved by utilizing traffic historical data to forecast the traffic flow which later supports travellers for a better journey planning.In this study, a new method that integrates Firefly algorithm (FA) with Least Squares Support Vector Machine (LSSVM) is proposed for short term traffic speed forecasting, which is later termed as FA-LSSVM.In particular, the Firefly algorithm which has the advantage in global search is used to optimize the hyper-parameters of LSSVM for efficient data training. …”
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Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi
Published 2018“…A Modified Particle Swarm Optimization (MPSO) algorithm, a Genetic Algorithm (GA), a modified fruit fly optimization algorithm (MFOA) and a simulated annealing (SA) algorithm were used to find the optimal solution. …”
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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…For model fit test (MSE and R-squared) both methods perform similar. For FRA NARMAX, PSO outperform than LLS in term of criterion fitness, MSE and correlation violation while in R-squared analysis both methods perform similar. …”
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A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network
Published 2024“…Methods: It is suggested that the objective function that will be optimized using NMM is the mean squared error of the range of all neighboring anchor nodes installed in the studied WSNs. …”
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Complex-valued nonlinear adaptive filters for noncircular signals
Published 2017“…The augmented CNGD has shown low Means Square Error (MSE) capabilities and have optimal performance than the conventional algorithm. …”
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Implementation and analysis of BBO algorithm for better damping of rotor oscillations of a synchronous machine
Published 2023Conference Paper
